Issue |
E3S Web Conf.
Volume 107, 2019
2019 4th International Conference on Sustainable and Renewable Energy Engineering (ICSREE 2019)
|
|
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Article Number | 02001 | |
Number of page(s) | 6 | |
Section | Power Electronic System | |
DOI | https://doi.org/10.1051/e3sconf/201910702001 | |
Published online | 05 July 2019 |
Fault detection and diagnosis of photovoltaic system using fuzzy logic control
1
School of Renewable and Clean Energy, North China Electric Power University, 102206, Beijing, China
2
The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, 102206, Beijing, China
3
Faculty of Engineering, Cairo University, Giza, Egypt
* Corresponding author: eng_sayed_002010@yahoo.com
Among several renewable energy resources, Solar has great potential to solve the world’s energy problems. With the rapid expansion and installation of PV system worldwide, fault detection and diagnosis has become the most significant issue in order to raise the system efficiency and reduce the maintenance cost as well as repair time. This paper presented a method for monitoring, identifying, and detecting different faults in PV array. This method is built based on comparing the measured electrical parameters with its theoretical parameters in case of normal and faulty conditions of PV array. For this purpose, three ratios of open circuit voltage, current, and voltage are obtained with their associated limits in order to detect eight different faults. Moreover, the fuzzy logic control FLC method is performed for studying the failure configuration and categorizing correctly the different faults occurred. The outcomes obtained by performing the different faults representing permanent and temporary faults demonstrated that the FLC was equipped to precisely identify the faults upon their occurring. Different simulated and experimental tests are conducted to demonstrate the performance of the proposed method.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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